Care seeking for diarrheal illnes: a systematic review and meta-analysis

Study characteristics

Fig 1. PRISMA diagram

PRISMA diagram.

Note: Unless otherwise noted, the data presented below represents 161 studies (210 or 211 stratified observation entries) in the primary, non-overlapping dataset that asked study participants whether or not the DID seek care for a past diarrheal illness.

We also have information on whether individuals would seek care for a hypothetical diarrheal illness from 27 studies (96 stratified observation entries).

Figure S1. Data coverage by geography

Number of stratified observation entries in the primary dataset at each administrative level by country. Countries with >10 observations displayed as 10.

Figure S2. Data coverage over time

Number of stratified observation entries in the primary dataset within different time periods. Year represents the year sampling was completed. Excludes 6 entries missing study dates.

Table 1. Study observation characteristics

variable	value	Total	Percent
Time care	Any care	170	82.1
	First source	29	14.0
	Prior to current visit	7	3.4
	Within 24 h	1	0.5
Self or child	Child	136	65.7
	Other	57	27.5
	Self	14	6.8
Recall time	14-30 days	143	69.1
	Not reported	35	16.9
	42-365 days	16	7.7
	2-7 days	13	6.3
Study population	Caregiver	112	54.1
	Other resident	58	28.0
	Head of household	23	11.1
	Caregiver of patient at health facility	9	4.3
	Patient at health facility	5	2.4
Outbreak described	No	189	91.3
Outbreak described	Yes	18	8.7
Mult choice	No	178	86.0
Mult choice	Yes	29	14.0
Location desc	Rural	82	39.6
	Urban	67	32.4
	Urban and Rural	50	24.2
	Peri-Urban	5	2.4
	IDP or Refugee Camp	2	1.0
	Urban and Peri-Urban	1	0.5
Income group	Lower middle income	96	46.4
	Upper middle income	43	20.8
	Low income	41	19.8
	High income	27	13.0
Case definition	Diarrhea	153	73.9
	Gastroenteritis or non-Vc etiologies	32	15.5
	Severe diarrhea or cholera	22	10.6

Care seeking trends in the unadjusted data

Note: “Hospitals or clinics” excludes individuals seeking care exclusively or explicitly at private hospitals/clinics, i.e., this includes location categories “Hospital/Clinic” (general) and “Public Hospital/Clinic” (more specific).

For multiple choice questions where there is more than one category of hospital/clinic, we take the largest proportion that sought care across them.

Figure S3. Proportion seeking care at a hospital or clinic by region

Figure S4. Proportion seeking care at a hospital or clinic by income group

Figure 2. Proportion seeking care at a hospital or clinic by observation characteristics

Figure S5. Proportion seeking care by study quality

Overall quality score is whether data is internally consistent + whether sample size was justified + whether the non-response was reported.

Figure 3. Relationship between care seeking and proportion under 5 years

Figure 4. Proportion seeking care by source in LMICs

Proportion seeking care by source and study characteristic

Figure S6. Income group

Figure S7. Case definition

Figure S8. Self or child

Adjusted estimates of care seeking at hospitals or clinics

Our goal here is to estimate the proportion of individuals that seek care when they or their child have diarrhea symptoms in LMICs. Since diarrhea symptoms vary, and some of the categories above had very few observations (e.g., cholera and “other”) we have grouped these into three broad categories of case definitions (below).

Diarrhea (3+ loose stools in past 24 hours OR general/no explicit definition provided)
Cholera (acute watery diarrhea of any severity, including resulting in death) or severe diarrhea (danger signs, dehydration, hospitalization, 1+ week duration, or death)
Gastroenteritis or other etiologies (diarrhea or vomiting, including specific etiologies eg rotavirus or e coli)

We build generalized linear models with a study-level random intercept following the approach of Wiens et al (2023) PLOS Medicine:

Unadjusted
Univariate models adjusted individually for:
1. Study methodology and population:
  - case definition
  - timing of care seeking
  - regarding self or child
  - recall period
  - multiple choice questions
  - study population
2. Contextual factors:
  - outbreak
  - urban/rural
Multivatiate model(s) adjusted for factors identified as significant but not confounding/collinear in univariate models.

NB: Here our observations represent data aggregated to study_id, country, and potential covariate stratifications, for a total of 146 unique observations corresponding to 114 studies. For studies with multiple choice questions, we take the maximum sample size and number seeking care for studies where there were multiple categories of “hospital/clinic” as possible answers.

Figure S9. Prior predictive checks

For the primary analysis, we chose priors that matched the distribution of the data. Specifically, we used a Normal(-0.6,1.5) prior on alpha, where the mean of the distribution (-0.67) matches the median of the observation data (0.339) in logit space. The resulting prior predictive distribution has a median of 0.34 and a mean of 0.37.

In sensitivity analyses, we shift the mean of the prior distribution on alpha up or right 20% in probability space (i.e., mean of -0.38 for the normal distribution in logit space, median of 0.41 for the observation data) and down or left 20% (i.e., mean of -0.99 for the normal distribution in logit space, median of 0.27 for the observation data).

Figure S10. Posterior distributions of the proportion of people seeking care

Table S1. Estimated proportion that seek care

Version	Proportion (%)
Unadjusted	39.3 (9.2 - 77.2)
Unadjusted - shift prior left	37 (8.1 - 75.6)
Unadjusted - shift prior right	42.7 (10.2 - 80.6)
Unadjusted - would you	71.1 (35.1 - 94.2)

FYI (not in paper): RE meta-anaysis a la ‘meta’

## Number of studies: k = 146
## Number of observations: o = 136822
## Number of events: e = 42388
## 
##                      proportion           95%-CI
## Random effects model     0.3455 [0.2941; 0.4007]
## 
## Quantifying heterogeneity:
##  tau^2 = 2.0548; tau = 1.4335; I^2 = 99.3% [99.2%; 99.3%]; H = 11.56 [11.26; 11.88]
## 
## Test of heterogeneity:
##              Q d.f. p-value
##  Wald 19392.96  145       0
##  LRT  32811.27  145       0
## 
## Details on meta-analytical method:
## - Random intercept logistic regression model
## - Maximum-likelihood estimator for tau^2
## - Logit transformation
## - Continuity correction of 0.5 in studies with zero cell frequencies
##   (only used to calculate individual study results)

Figure 5. Forest plots

The “estimated” results are the study-level props from the model that includes pop_cat and case_cat.

## I2: 99.9875, 99.98791, 99.98833, ; tau2: 0.77052, 0.79662, 0.8252,

Factors associated with variation in care seeking at hospitals or clinics

Table S2. Univariate analyses - did you

Odds of actually seeking care for diarrhea for each indicated variable, not adjusting for any other variables.

Variable	Category	Odds ratio
case_cat	Diarrhea	1 [Reference]
	Gastroenteritis or non-Vc etiologies	2.39 (0.76 - 5.72)
	Severe diarrhea or cholera	3.06 (1.4 - 5.95)	**
location_desc	Non-urban	1 [Reference]
	Urban	1.15 (0.64 - 1.82)
	Urban and non-urban	1.54 (0.72 - 2.87)
mult_choice	0	1 [Reference]
mult_choice	1	1.11 (0.56 - 1.93)
outbreak_desc	0	1 [Reference]
outbreak_desc	1	3.1 (1.16 - 7.01)	**
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	8.28 (2.15 - 21.49)	**
	Head of household	1.05 (0.51 - 1.93)
	Other resident	1.27 (0.68 - 2.18)
recall_time	over30_orNA	1 [Reference]
recall_time	under30	0.36 (0.2 - 0.61)	**
self_or_child	Child	1 [Reference]
	Other	0.88 (0.48 - 1.44)
	Self	0.92 (0.24 - 2.34)
time_care	Any care	1 [Reference]
	First source	0.88 (0.46 - 1.55)
	Prior to current visit	1.42 (0.16 - 5.63)

FYI (not in paper): Univariate analyses - would you

Odds of hypothetically seeking care for diarrhea for each indicated variable, not adjusting for any other variables.

Variable	Category	Odds ratio
case_cat	Diarrhea	1 [Reference]
	Gastroenteritis or non-Vc etiologies	22.7 (0.78 - 121.45)
	Severe diarrhea or cholera	9.52 (1.69 - 29.66)	**
location_desc	Non-urban	1 [Reference]
	Urban	2.33 (0.32 - 8.28)
	Urban and non-urban	1.21 (0.15 - 4.35)
mult_choice	0	1 [Reference]
mult_choice	1	6.79 (1.12 - 23.74)	**
outbreak_desc	0	1 [Reference]
outbreak_desc	1	2.11 (0.21 - 8.92)
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	21.57 (0.74 - 120.01)
	Head of household	0.81 (0.18 - 2.39)
	Other resident	9.84 (1.63 - 32.54)	**
recall_time	over30_orNA	1 [Reference]
recall_time	under30	2.54 (0.07 - 14.93)
self_or_child	Child	1 [Reference]
	Other	0.81 (0.12 - 3.05)
	Self	9.06 (1.41 - 30.75)	**
time_care	Any care	1 [Reference]
	First source	2.52 (0.07 - 13.53)
	Prior to current visit	NA

Table S3. Sub-analyses by age: studies that are either only adults or only children

Odds of seeking care for diarrhea for adults vs. children, not adjusting for any other variables. We have 130 observations total here.

Variable	Category	Odds ratio
prop_five	0	1 [Reference]
prop_five	1	1.07 (0.51 - 2.07)

Table S4. Sub-analyses by age: studies with care seeking stratified by age

Odds of seeking care for diarrhea for adults vs. children, not adjusting for any other variables. We have data from 7 studies that report healthcare seeking at a hospital/clinic by age groups under/over five for LMICs.

Variable	Category	Odds ratio
prop_five	0	1 [Reference]
prop_five	1	1.75 (0.29 - 6.04)

FYI (not in paper): RE meta-analysis a la ‘meta’ by age

## Number of studies: k = 14
## Number of observations: o = 26954
## Number of events: e = 7955
## 
##                      proportion           95%-CI
## Random effects model     0.3165 [0.1729; 0.5062]
## 
## Quantifying heterogeneity:
##  tau^2 = 2.0926; tau = 1.4466; I^2 = 99.2% [99.0%; 99.3%]; H = 10.96 [9.99; 12.02]
## 
## Test of heterogeneity:
##             Q d.f. p-value
##  Wald 1561.41   13       0
##  LRT  1775.73   13       0
## 
## Results for subgroups (random effects model):
##                 k proportion           95%-CI  tau^2    tau       Q   I^2
## prop_five = 0   7     0.2844 [0.1079; 0.5665] 2.4459 1.5639 1233.24 99.5%
## prop_five = 1   7     0.3461 [0.1583; 0.5984] 1.6565 1.2870  255.83 97.7%
## 
## Test for subgroup differences (random effects model):
##                   Q d.f. p-value
## Between groups 0.13    1  0.7218
## 
## Details on meta-analytical method:
## - Random intercept logistic regression model
## - Maximum-likelihood estimator for tau^2
## - Logit transformation

FYI (not in paper): Meta-regression a la ‘metafor’ by age

Residual heterogeneity (tau2) is the same between groups

## 
## Mixed-Effects Model (k = 14; tau^2 estimator: REML)
## 
## tau^2 (estimated amount of residual heterogeneity):     2.690 (SE = 1.102)
## tau (square root of estimated tau^2 value):             1.640
## I^2 (residual heterogeneity / unaccounted variability): 99.99%
## H^2 (unaccounted variability / sampling variability):   12778.89
## R^2 (amount of heterogeneity accounted for):            0.00%
## 
## Test for Residual Heterogeneity:
## QE(df = 12) = 66652.799, p-val < .001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.246, p-val = 0.620
## 
## Model Results:
## 
##            estimate     se    zval   pval   ci.lb  ci.ub    
## intrcpt      -0.889  0.620  -1.433  0.152  -2.105  0.327    
## prop_five     0.436  0.878   0.496  0.620  -1.285  2.157    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Allowing amounts of residual heterogeneity (tau2) to be different between groups

## 
## Multivariate Meta-Analysis Model (k = 14; method: REML)
## 
## Variance Components:
## 
## outer factor: study_id  (nlvls = 7)
## inner factor: prop_five (nlvls = 2)
## 
##            estim   sqrt  k.lvl  fixed  level 
## tau^2.1    2.977  1.726      7     no      0 
## tau^2.2    2.401  1.550      7     no      1 
## 
## Test for Residual Heterogeneity:
## QE(df = 12) = 66652.799, p-val < .001
## 
## Test of Moderators (coefficient 2):
## QM(df = 1) = 0.245, p-val = 0.620
## 
## Model Results:
## 
##            estimate     se    zval   pval   ci.lb  ci.ub    
## intrcpt      -0.889  0.653  -1.362  0.173  -2.168  0.390    
## prop_five     0.435  0.878   0.495  0.620  -1.286  2.156    
## 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Table S5. Tests for potential confounding

In analyses below, the dependent variable is listed in the header.

self_or_child (self/adult vs child)

Variable	Category	Odds ratio
case_cat	Diarrhea	1 [Reference]
	Gastroenteritis or non-Vc etiologies	4.38 (0.02 - 34.05)
	Severe diarrhea or cholera	0.74 (0.01 - 4.2)
mult_choice	0	1 [Reference]
mult_choice	1	0.38 (0.01 - 1.94)
outbreak_desc	0	1 [Reference]
outbreak_desc	1	0.55 (0.01 - 3.13)
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	1.96 (0.02 - 12.1)
	Head of household	1.97 (0.01 - 12.41)
	Other resident	73.54 (9.33 - 282.68)	**
recall_time	over30_orNA	1 [Reference]
recall_time	under30	0.2 (0.03 - 0.73)	**
time_care	Any care	1 [Reference]
	First source	0.36 (0.01 - 1.9)
	Prior to current visit	2.22 (0.02 - 14.27)

outbreak_desc

Variable	Category	Odds ratio
case_cat	Diarrhea	1 [Reference]
	Gastroenteritis or non-Vc etiologies	1.94 (0.02 - 11.69)
	Severe diarrhea or cholera	24.38 (4.04 - 88.67)	**
mult_choice	0	1 [Reference]
mult_choice	1	1.83 (0.17 - 7.68)
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	1.44 (0.01 - 8.82)
	Head of household	5.79 (0.79 - 21.78)
	Other resident	1.59 (0.14 - 6.08)
recall_time	over30_orNA	1 [Reference]
recall_time	under30	0.09 (0.01 - 0.26)	**
self_or_child	Child	1 [Reference]
	Other	2.26 (0.34 - 7.82)
	Self	1.61 (0.02 - 9.22)
time_care	Any care	1 [Reference]
	First source	0.49 (0.03 - 1.94)
	Prior to current visit	2.23 (0.02 - 14)

case_cat

Severe diarrhea or cholera

Variable	Category	Odds ratio
mult_choice	0	1 [Reference]
mult_choice	1	1.47 (0.11 - 6.12)
outbreak_desc	0	1 [Reference]
outbreak_desc	1	25.37 (3.61 - 92.94)	**
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	5.49 (0.14 - 29.16)
	Head of household	4.77 (0.58 - 18.2)
	Other resident	4.56 (0.57 - 16.57)
recall_time	over30_orNA	1 [Reference]
recall_time	under30	0.03 (0.01 - 0.1)	**
self_or_child	Child	1 [Reference]
	Other	4.27 (0.71 - 14.5)
	Self	1.37 (0.01 - 8.2)
time_care	Any care	1 [Reference]
	First source	1.12 (0.13 - 3.86)
	Prior to current visit	9.63 (0.19 - 54.96)

Gastroenteritis or non-V cholerae

Variable	Category	Odds ratio
mult_choice	0	1 [Reference]
mult_choice	1	0.84 (0.05 - 3.78)
outbreak_desc	0	1 [Reference]
outbreak_desc	1	1.17 (0.01 - 6.88)
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	10.76 (0.26 - 57.17)
	Head of household	0.66 (0.01 - 3.76)
	Other resident	19.97 (2.96 - 74.9)	**
recall_time	over30_orNA	1 [Reference]
recall_time	under30	0.17 (0.02 - 0.58)	**
self_or_child	Child	1 [Reference]
	Other	12.89 (1.92 - 46.55)	**
	Self	2.19 (0.02 - 14.11)
time_care	Any care	1 [Reference]
	First source	0.59 (0.04 - 2.38)
	Prior to current visit	2.98 (0.02 - 18.84)

Table S6. Sub-analyses

Vc or severe diarrhea

Is there still an effect of being in an outbreak when we subset the data to just case definitions specific to cholera or severe diarrhea (including death)?

Variable	Category	Odds ratio
outbreak_desc	0	1 [Reference]
outbreak_desc	1	2.01 (0.37 - 6.38)

Diarrhea

Is there still an effect of recall period when we subset the data to just case definitions for general diarrhea (not severe or resulting in death)?

Variable	Category	Odds ratio
recall_time	over30_orNA	1 [Reference]
recall_time	under30	0.72 (0.34 - 1.31)

Table 2. Factors associated with variation in care seeking rates

Odds that an individual seeks care for themselves or their child overall or by alternate case definitions, adjusting for study respondent.

Model including study population and case definition
Variable	Category	Odds ratio
case_cat	Diarrhea	1 [Reference]
	Gastroenteritis or non-Vc etiologies	2.2 (0.65 - 5.5)
	Severe diarrhea or cholera	2.99 (1.32 - 5.83)	**
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	6.94 (1.95 - 17.82)	**
	Head of household	0.95 (0.47 - 1.7)
	Other resident	1.01 (0.53 - 1.76)

FYI (not in paper): Factors associated with variation in hypothetical care seeking rates

Odds that an individual hypothetically seeks care for themselves or their child overall or by alternate case definitions, adjusting for study respondent.

Model including study population and case definition
Variable	Category	Odds ratio
case_cat	Diarrhea	1 [Reference]
	Gastroenteritis or non-Vc etiologies	14.72 (0.19 - 91.71)
	Severe diarrhea or cholera	5.17 (0.59 - 20.53)
pop_cat	Caregiver	1 [Reference]
	Caregiver of patient at health facility	14.45 (0.2 - 94.48)
	Head of household	0.75 (0.15 - 2.19)
	Other resident	5.21 (0.52 - 21.5)

Table S7. Stratified estimates of care seeking by category

Stratifications correspond to questions that refer to care seeking for a caregiver.

Version	Model	Variable	Proportion (%)
Main result	1	Unadjusted	39.3 (9.2 - 77.2)
	2	Diarrhea	38.6 (8.4 - 77.1)
	2	Gastroenteritis or non-Vc etiologies	69.8 (24.3 - 98.9)
	2	Severe diarrhea or cholera	79.5 (37.4 - 99.2)
	3	Adjusted for methods	38.3 (8.6 - 76.5)
Shift prior left	1	Unadjusted	37 (8.1 - 75.6)
	2	Diarrhea	35.7 (7.3 - 74.4)
	2	Gastroenteritis or non-Vc etiologies	66.8 (20.6 - 98.8)
	2	Severe diarrhea or cholera	76.5 (32.2 - 99.1)
	3	Adjusted for methods	35.8 (7.2 - 73.6)
Shift prior right	1	Unadjusted	42.7 (10.2 - 80.6)
	2	Diarrhea	41.3 (9.6 - 78.7)
	2	Gastroenteritis or non-Vc etiologies	71.8 (26.2 - 98.9)
	2	Severe diarrhea or cholera	81.6 (41 - 99.5)
	3	Adjusted for methods	41.5 (10 - 79.1)

FYI (not in paper): Sub-grpup analysis a la ‘meta’ by case definition

## Number of studies: k = 146
## Number of observations: o = 136822
## Number of events: e = 42388
## 
##                      proportion           95%-CI
## Random effects model     0.3455 [0.2941; 0.4007]
## 
## Quantifying heterogeneity:
##  tau^2 = 2.0548; tau = 1.4335; I^2 = 99.3% [99.2%; 99.3%]; H = 11.56 [11.26; 11.88]
## 
## Test of heterogeneity:
##              Q d.f. p-value
##  Wald 19392.96  145       0
##  LRT  32811.27  145       0
## 
## Results for subgroups (random effects model):
##                                                  k proportion           95%-CI
## case_cat = Diarrhea                            122     0.3378 [0.2815; 0.3991]
## case_cat = Severe diarrhea or cholera           16     0.3721 [0.2200; 0.5545]
## case_cat = Gastroenteritis or non-Vc etiol ...   8     0.3927 [0.3092; 0.4830]
##                                                 tau^2    tau        Q   I^2
## case_cat = Diarrhea                            2.1470 1.4653 16670.15 99.3%
## case_cat = Severe diarrhea or cholera          2.2102 1.4867  2436.73 99.4%
## case_cat = Gastroenteritis or non-Vc etiol ... 0.2267 0.4762   209.81 96.7%
## 
## Test for subgroup differences (random effects model):
##                   Q d.f. p-value
## Between groups 1.08    2  0.5817
## 
## Details on meta-analytical method:
## - Random intercept logistic regression model
## - Maximum-likelihood estimator for tau^2
## - Logit transformation
## - Continuity correction of 0.5 in studies with zero cell frequencies
##   (only used to calculate individual study results)

FYI (not in paper): Meta-regression a la ‘metafor’ by case definition

To do this with logit(proportion) as outcome, need to drop Cuban study where 100% sought care.